Metadata-Version: 2.0
Name: azureml-mlflow
Version: 1.35.0
Summary: Contains the integration code of AzureML with Mlflow.
Home-page: https://docs.microsoft.com/python/api/overview/azure/ml/?view=azure-ml-py
Author: Microsoft Corp
License: Proprietary https://aka.ms/azureml-preview-sdk-license 
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: Other/Proprietary License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Operating System :: Microsoft :: Windows
Classifier: Operating System :: MacOS
Classifier: Operating System :: POSIX :: Linux
Description-Content-Type: text/x-rst
Provides-Extra: deployments
Requires-Dist: azureml-core (~=1.35.0)
Requires-Dist: jsonpickle
Requires-Dist: mlflow-skinny
Provides-Extra: deployments
Requires-Dist: flask; extra == 'deployments'
Requires-Dist: numpy; extra == 'deployments'
Requires-Dist: pandas; extra == 'deployments'

Microsoft Azure Machine Learning Tracking server plugin for Python
==================================================================

The azureml-mlflow package contains the integration code of AzureML with MLflow.
MLflow (https://mlflow.org/) is an open-source platform for tracking machine learning experiments and managing models.
You can use MLflow logging APIs with Azure Machine Learning so that metrics and artifacts are logged to your Azure
machine learning workspace.

Usage
-----

Within an `AzureML Workspace <https://docs.microsoft.com/python/api/overview/azure/ml/intro?view=azure-ml-py>`_,
add the code below to use MLflow.

.. code-block:: python

   import mlflow
   from azureml.core import Workspace

   workspace = Workspace.from_config()

   mlflow.set_tracking_uri(workspace.get_mlflow_tracking_uri())

More examples can be found at https://aka.ms/azureml-mlflow-examples.




